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@@ -4,29 +4,31 @@ tags:
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  model-index:
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  - name: trocr-base-handwritten-OCR-handwriting_recognition_v2
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  results: []
 
 
 
 
 
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  ---
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- <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- should probably proofread and complete it, then remove this comment. -->
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-
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  # trocr-base-handwritten-OCR-handwriting_recognition_v2
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- This model is a fine-tuned version of [microsoft/trocr-base-handwritten](https://huggingface.co/microsoft/trocr-base-handwritten) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.2470
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  - Cer: 0.0360
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  ## Model description
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- More information needed
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  ## Intended uses & limitations
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- More information needed
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  ## Training and evaluation data
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- More information needed
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  ## Training procedure
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@@ -55,4 +57,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.26.0
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  - Pytorch 1.12.1
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  - Datasets 2.8.0
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- - Tokenizers 0.12.1
 
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  model-index:
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  - name: trocr-base-handwritten-OCR-handwriting_recognition_v2
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  results: []
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+ language:
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+ - en
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+ metrics:
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+ - cer
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+ pipeline_tag: image-to-text
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  ---
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  # trocr-base-handwritten-OCR-handwriting_recognition_v2
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+ This model is a fine-tuned version of [microsoft/trocr-base-handwritten](https://huggingface.co/microsoft/trocr-base-handwritten).
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  It achieves the following results on the evaluation set:
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  - Loss: 0.2470
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  - Cer: 0.0360
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  ## Model description
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+ For more information on how it was created, check out the following link: https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/blob/main/Optical%20Character%20Recognition%20(OCR)/Handwriting%20Recognition/Handwriting%20Recognition_v2/Mini%20Handwriting%20OCR%20Project.ipynb
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  ## Intended uses & limitations
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+ This model is intended to demonstrate my ability to solve a complex problem using technology.
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  ## Training and evaluation data
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+ Dataset Source: https://www.kaggle.com/datasets/ssarkar445/handwriting-recognitionocr
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  ## Training procedure
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  - Transformers 4.26.0
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  - Pytorch 1.12.1
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  - Datasets 2.8.0
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+ - Tokenizers 0.12.1